---
title: "Dashboards at EVANS UW"
author: "Great student"
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    social: menu
    source_code: embed
---

```{r setup, include=FALSE}
#imoprt libraries
library(ggplot2)
library(plotly)
library(RColorBrewer)
library(leaflet)
library(rio)
library(leafsync)
library(sf)
library(flexdashboard)


############# CHART A CODE

gitlink='https://github.com/RSGriggs/543_proj/raw/main/'
#establilsh value for dataset desired
spend='Activity_spending.xlsx'
#query excel and store as value 'act'
spend2=paste0(gitlink, spend)
#store value as datatable
spenddata=import(spend2)
#generate data frame
SpendingFrame=as.data.frame.matrix(spenddata)
#Generate base version of plot
spend1=ggplot(data=SpendingFrame,
                  aes(x=Party_Size,
                  y=Avg_Spending,
                  fill=Destination)) +
              geom_bar(stat="identity",
                      fun = 'mean',
                      position='dodge') +

                     labs(title = "Average Spending by Venue",
                          subtitle = "Catagorical and Numerical Plot",
                          y = "Average $ Spent Per person",
                          x = "Number of People in Party") +
#change color
              scale_fill_brewer(palette = "Pastel2" )


############ CHART B CODE


#establish link to git repository
gitlink='https://github.com/RSGriggs/543_proj/raw/main/'
#establilsh value for dataset desired
activity='activity.xls'
#query excel and store as value 'act'
act=paste0(gitlink, activity)
#store value as datatable
actdata=import(act)
# determine the number of unique values in time spent on activities
length(unique(actdata$timespent))
#summarize time spent at attractions
summary(actdata$timespent)
#check asymmetry
library(DescTools)
Skew(actdata$timespent,na.rm = T,conf.level = 0.95, ci.type = "bca",R=2500)
# shape
Kurt(actdata$timespent,na.rm = T,conf.level = 0.95, ci.type = "bca",R=2500)
#set width of column
WIDTH=15
time1= ggplot(actdata,aes(x=timespent)) +
  labs(title = "Time spent at public attractions.",
       y = "Percent Visitors",
       x = "Minutes spent at attraction")
time2= time1 + geom_histogram(binwidth = WIDTH,aes(y=stat(density*WIDTH)))
time3= time2 + scale_y_continuous(labels = scales::percent_format())
MEAN=summary(actdata$timespent)[4]
time4= time2 + geom_vline(xintercept = MEAN)


############# CHART C CODE


TestMapFile='https://github.com/RSGriggs/543_proj/raw/main/us-states.json'
TestMap=read_sf(TestMapFile)
str(TestMap)
#load merge data set 
CSVLink='https://github.com/RSGriggs/543_proj/raw/main/Smithsfavoritestates.csv'
CSVData=read.csv(CSVLink)
str(CSVData)
T1=ggplot(data=TestMap) + geom_sf(fill='grey90',
                                     color=NA) + theme_classic()
                                     MapVariables=merge(TestMap,
                   CSVData, 
                   by='name')

SMap= T1 + geom_sf(data=MapVariables,
                       aes(fill=Data),
                       color=NA)
SMap2 = SMap + scale_fill_gradient(low = 'gold',
                             high= 'black')
SMap3 = SMap2 + theme_void()
SMap4 = SMap3 + labs(title="Smith Rates the U.S. States by Arbitrary Preference.",
                     subtitle = 'The best are the brightest.',
                     x = NULL, 
                     y = NULL,
                     caption = 'R. Smith Griggs')
SMap5 = SMap4 + theme(plot.caption = element_text(hjust = 1), 
                      plot.title = element_text(hjust = 0.5))
```

Column {data-width=200}
-----------------------------------------------------------------------

### Univariate

```{r}
spend1
```


### Multivariate

```{r}
time4
```

Row {data-width=400}
-----------------------------------------------------------------------
### Map
```{r}
SMap5
```